Software Engineer II - Data & Applications (Hybrid, Clinton PA)

Haemonetics•Clinton, PA

8d•Hybrid

About The Position

We are constantly looking to add to our core talent. If you are seeking a career that is challenging and rewarding, a work environment that is diverse and dynamic, look no further — Haemonetics is your employer of choice. Job Details We are seeking a Software Engineer II – Data & Applications to design, develop, and support full-stack data-driven applications across edge and cloud environments. This role blends software engineering and data engineering disciplines, focusing on front-end interfaces, backend APIs, data pipelines, and real-time streaming systems. You will play a key role in developing production-quality systems, supporting edge-to-cloud data integration, and collaborating with cross-functional teams spanning manufacturing, data science, and operations. The ideal candidate is self-motivated, comfortable working across multiple layers of the technology stack, and ready to help shape the company’s data architecture. This role may require up to 50% travel and is Hybrid (3 days per week) in our Clinton, PA Manufacturing Facility.

Requirements

2–5 years of professional software engineering experience
Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Data Science, or related field (or equivalent experience)
Proficiency in backend programming languages such as Python, Java, C#, or Go
Working experience with front-end frameworks (e.g., React, Angular, or Vue )
Solid understanding of RESTful API design , versioning, and authentication methods
Experience designing and maintaining relational and non-relational databases
Familiarity with streaming technologies (Kafka, MQTT, or similar) and data pipeline design
Experience developing on Linux systems, including scripting and performance debugging
Strong understanding of software architecture, data modeling, and integration concepts
Excellent problem-solving, analytical, and debugging skills
Ability to balance multiple projects and collaborate effectively across teams

Nice To Haves

Hands-on experience with Litmus Edge or other edge computing frameworks
Tulip Interfaces implementation and app development experience
Experience with containerization and orchestration (Docker, Kubernetes)
Familiarity with cloud platforms (AWS, Azure, GCP) and cloud-native data tools
Experience with monitoring and observability tools (Prometheus, Grafana, ELK)
Exposure to CI/CD pipelines , GitOps, and automated testing frameworks
Experience integrating or deploying machine learning models in production environments
Understanding of industrial IoT (IIoT) data protocols and edge-to-cloud architectures

Responsibilities

Design, implement, and maintain full-stack applications with a focus on performance, scalability, and reliability
Develop and manage APIs (REST, gRPC, GraphQL) for internal and external system communication
Architect, build, and optimize data pipelines and ETL processes (batch and streaming)
Work with message buses and data streaming frameworks (Kafka, MQTT, etc.)
Design and evolve database schemas (SQL and NoSQL) to support application and analytics needs
Deploy and support applications across Linux-based edge and cloud environments
Integrate data from edge computing platforms (Litmus Edge preferred) with central systems
Collaborate with data scientists and analytics engineers to support model deployment and data services
Implement observability (logging, metrics, monitoring) for data and application reliability
Participate in code reviews, architecture reviews, and cross-team technical discussions
Mentor junior engineers and support their technical development
Travel (up to 50%) to support integration and deployment at North American sites